BEKhealth’s Post

There are multiple ways generative artificial intelligence could benefit biopharma companies, including with their clinical trials. It was great talking to Rune Bergendorff about this topic, as he's been helping companies in Europe and the United States explore how they might implement GenAI. Check out this BioSpace Q&A to see what he had to say. #clinicaltrials #biopharma #biospace

Keeping up with the pace of innovation in AI and clinical research can be a daunting task. AI will no doubt streamline various aspects of clinical trials, from patient recruitment and data analysis to drug discovery and safety monitoring. With AI-driven algorithms, researchers can sift through vast amounts of medical literature and patient data to identify patterns, predict outcomes, and personalize treatments, leading to more efficient and effective healthcare interventions. As AI continues to evolve, keeping patients at the center of our efforts will help to ensure we remain on the right path. Thanks to Stephen Pyke for sharing your insights! #AI #ClinicalTrials #Innovation #LifeSciences Learn more: https://lnkd.in/ecdCVQdc

I recently had the pleasure of interviewing Dr. Rama Kondru, CEO of Veridix AI, discussing his personal journey as well as the company’s innovative strides in the intersection of AI and life sciences. Here are some of the key take-aways: 🔸1. Integration of AI in Clinical Research: Dr. Kondru's background in computational sciences and his experience at Johnson & Johnson led him to recognize the potential of AI to revolutionize drug development and improve patient care through various phases. 🔸2. Enhancing Patient Outcomes with AI: At Veridix AI, AI is seen as a transformative tool in clinical research, particularly in speeding up clinical trials and making them more patient-centric, which enhances patient outcomes. 🔸3. Technological Innovations: Veridix AI is at the forefront of using generative AI models and machine learning to automate and optimize clinical trial processes such as protocol design, patient narratives, and trial setup, aiming to reduce timelines and improve precision. 🔸4. Efficiency and Data Integrity: AI enhances trial efficiency by optimizing trial setup and data analysis, while AI-driven tools ensure data integrity and quality through comprehensive real-time monitoring and standardized data management. 🔸5. Overcoming Challenges: The integration of AI into clinical research faced obstacles such as resistance to new technologies and the need for compliance. Veridix AI addressed these through continuous education and adhering to regulatory standards. 🔸6. Ethical Considerations: Veridix AI prioritizes ethical AI use by maintaining transparency and incorporating safeguards to protect patient safety and outcomes. 🔸7. Future Trends and Strategic Partnerships: Dr. Kondru highlighted the importance of strategic partnerships in staying ahead of AI applications in clinical research. Emerging AI trends like automation of medical text and improved patient enrollment strategies are expected to significantly impact the field. 👇Full interview link provided in the comments section.

How can we use Gen AI in life sciences?  Aside from the obvious day-to-day efficiencies that we’re seeing in most fields, one possible application in this sector could be to improve protocol design. This involves using synthetic data to simulate outcomes for distinct patient groups based on what we know from past trials. Ultimately, this could help to predict patient outcomes, refine the parameters of a trial and could even shorten lengthy timelines, meaning reduced time-to-market.  You can find out more in this blog: https://rebrand.ly/9w3ydg7 What are do you see Gen AI benefitting the most?  #GenAI #ClinicalTrials #LifeSciences #Medidata

Industry News: A study published in the NEJM Group’s AI-focused publication reveals that generative AI can speed up clinical trial enrollment for just 11 cents per patient, compared to traditional methods costing thousands of dollars. Share your thoughts on what this could mean for the future of pharma in the comments below! Read more about this groundbreaking study here: https://loom.ly/ItBvhu8 #ClinicalTrials #AI #Innovation

New research demonstrates that a customized AI application can significantly streamline the clinical trial patient identification process, according to Mass General Brigham. The study found: ● AI Accuracy was 97.9% - 100%. ● Human Staff Accuracy was 91.7% - 100%. The researchers also found that the cost of AI review averaged 11 cents per patient vs. hundreds of dollars for traditional methods. But AI also poses multiple known risks. We suggest the safest path forward is to implement strong data loss prevention and acceptable use policies for AI first, and then ensure that experienced teams are overseeing its use. Read the article: https://lnkd.in/gfD3gha6 #AI #HealthcareInnovation #ClinicalTrials #AIforbiotechnology #biotech #biotechnology

AI vs life-long learning and reality. https://lnkd.in/g7Uucb2q If you have an AI interest, I highly recommend reading this item, as it perhaps highlights a huge opportunity, and relates to trustworthiness. I am hopeful this shakes the core to spur meaningful work; thoughts to share ?

Looking for evidence-based research into generative AI's role in powering digital twins for drug discovery and clinical trials?    This recent publication on PubMed elucidates the innovation, detailing how digital twins—virtual simulations of physiological and biological processes—can dramatically accelerate drug development and personalise patient care. It's a testament to how AI is not just transforming our operational capabilities but is also deepening our understanding of complex diseases.    https://lnkd.in/ezEmhF82    #clinicaltrial  #ideapharma  #pharmaceuticalinnovation  #positioning  #AI 

How will AI transform health care? In this week’s episode of What Now? AI, #UofT experts Christine Allen and Andrew Pinto join hosts Beth Coleman and Rahul Krishnan to discuss the game-changing potential of AI in drug development & primary care. 🎧 uoft.me/wnai3

We all want to make #clinicaltrials more efficient, effective and inclusive. AI can help. ZS’s Ronald Du, James Gordon, Ashley Phuong and Shelley Liu share how members of our Clinical Feasibility Consortium say #AI can optimize trial design and planning. I found their observation that organizations can use AI to bridge the gap between expected outcomes and actual results to be particularly insightful. Of course, incorporating AI in trial design and planning won’t be as easy as flipping a switch. Some team members may be reluctant to embrace AI, as they could have misperceptions around its value, disagreements about who should own and control it and questions about AI’s impact on human identity and organizational roles. I encourage you to try the three strategies consortium members suggest for overcoming these concerns to drive AI adoption.  https://lnkd.in/g_gEbK5U